Description:

Design and oversee deployment of data architecture and pipelines for structured and unstructured data.
Develop technical tools for data cleansing, organization, and transformation using ML and data-engineering techniques.
Partner with product and AI teams to define evaluation metrics and establish ground truth labeling standards.
Implement automated evaluation infrastructure for measuring AI agent performance and create reporting dashboards.
Create design standards and quality assurance processes for data systems and recommend optimizations.
Collaborate with cross-functional teams and mentor junior engineers on data engineering practices.

Requirements:

9+ years of experience in designing and building production data pipelines and data warehousing.
3+ years of experience with ML systems, model validation, and automated testing.
Proven track record in deploying and maintaining large-scale data systems in production.
Ability to design scalable data architectures with experience in cloud platforms (GCP, AWS).
Familiarity with AI/ML evaluation frameworks and understanding of model performance tracking.
Strong communication skills and ability to drive technical conversations across teams.
Experience on the ServiceNow platform is a plus.

Flexible work personas (remote, in-office, or hybrid) based on job requirements.
Equal opportunity employer committed to inclusivity and accessibility for all candidates.

Skills